The advent of the information age has resulted in systems of automation and a variety of software applications for major business functions such as accounting, payroll, sales, manufacturing, logistics, and so on. Over time, each of these applications generates a tremendous amount of data, information and content within the business context of the particular application. The content within each of these applications may be classified as unstructured and structured content.
Unstructured content is essentially data or files without an organizational structure that defines the content. Common examples of unstructured content include text documents, images, presentation materials, drawings, email, video and audio files.
Structured content is data transformed through a series of business rules, programming logic, and organizational constructs as defined by an authoring application. Structured content is often a virtual, logical representation of content that is not physically stored on a network, but rather instantiated by an application upon request. While unstructured content is typically exposed and registered in file directories for users and applications to search and access, structured content is typically embedded within an application lying behind proprietary, application-specific schemes and mechanisms for defining, accessing, organizing and displaying content. Because structured content is embedded within each corresponding application, it is difficult to list, organize and access structured content in a combined view. Examples of applications generating structured content include customer relationship management (CRM) software, enterprise resource planning software, supply chain management software, general ledger/financial software, human resources software, and reporting software.
A specific class of applications devoted to creation and management of structured content are business intelligence systems. Business intelligence systems represents a class of software products that transform data into structured content to assist individuals, such as employees, in the discovery of trends, patterns, and associations to better understand operations, opportunities, and market trends. Business intelligence software products currently utilize different architectures, application logic, business rules, and security mechanisms for generating structured content.
Because different structured content applications have different features and functionality, many enterprises deploy a “best of breed” approach by installing specialized applications that handle a specific group of business processes.
However, current structured content systems utilize a unique, proprietary security and access mechanism, and generate structured content according to the unique business rules, features, and data available in the context of the application. The “learning curve” required to proficiently utilize each system can be high. This often results in an inability or reluctance by the knowledge workers to utilize the full data resources within the enterprise.
Enterprises have therefore become frustrated with the inability to locate, access, and align structured content to business processes, and analytic thought processes necessary to work more effectively and efficiently. For example, sales information may be available within application “A,” inventory information is only available in application “B,” and costs may be accessible only in application “C.” In essence, each application has imposed an architectural and contextual boundary to the structured content offered. Therefore, an employee needing all three types of structured content must know where to find each application, remember multiple passwords, locate the appropriate structured content within the application, and switch between the different application interfaces to use the content. Furthermore, if an employee intends to integrate the information into one report or view, the employee would have to export the information out of each system and bring it into some common format (e.g., a spreadsheet) and then generate rules to integrate the information (e.g., formulas in a spreadsheet).